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Digital transformation to the Pharma 4.0 paradigm moves forward in process development and clinical and commercial manufacturing.
Pharmaceutical manufacturers should be familiar with the terms “Smart Factory,” or “Pharma 4.0,” which is the International Society for Pharmaceutical Engineering (ISPE)’s trademarked name for Industry 4.0 in pharmaceutical manufacturing. Pharma 4.0 moves beyond automation and strives to use digital technology, including the Industrial Internet of Things (IIoT) and software tools that mine data from large datasets in the cloud, to increase productivity. These tools can be implemented in pharmaceutical process development and in clinical and commercial manufacturing, and many manufacturers in the bio/pharma industry are using them to aid in digital transformation. Yet, misconceptions and limited knowledge remain a barrier for some because digitalization is a new way of thinking and working.
At its essence, Pharma 4.0 is a paradigm shift, says Gilad Langer, industry practice lead at Tulip Interfaces. He is currently leading an ISPE Pharma 4.0 Community of Practice subgroup that is preparing to publish a Pharma 4.0 best practice guide in 2023. Industry 4.0 equipment—such as a smart sensor—is autonomous (i.e., plug and produce) and collaborative (i.e., communicates with other equipment or with people using the IIoT), explains Langer. “Pharma 4.0 is a concept that, if adopted wholly and effectively, has the promise of an order-of-magnitude productivity increase,” he asserts.
“The connectivity of smart devices changes where, how, and by whom decisions are made in the manufacturing process,” adds Sandra K. Rodriguez, senior industry analyst at life-science consultancy Axendia. “The efficiencies gained by smart manufacturing techniques cannot be achieved using paper-based, paper-on-glass, or manual processes that rely on people. The use of manufacturing execution systems (MES) is a key component in smart manufacturing. People supervise the manufacturing process in the new standard, as opposed to driving it.”
Axendia researched the state of digital transformation in life sciences manufacturing (1) and found that 43% of respondents (representing
pharmaceutical, biotech, and medical device companies) are currently undergoing digital transformation, reports Rodriguez.
Business drivers for digital transformation initiatives include “speed to market, enabling data-driven decisions, enhanced operational excellence, improved regulatory compliance, and addressing sustainability goals,” adds Mark-John Bruwer, senior director of strategic product marketing, pharma, at AspenTech. Digital transformation is being accelerated by the need for more supply chain agility, the increase in remote work, and the tight labor market, he adds. “Pharma companies are increasingly adopting digital tools for continuous process verification (CPV), advanced planning and scheduling, electronic batch records, convergence of information technology (IT) and operational technology (OT) functions, process analytical technology, and predictive maintenance,” says Bruwer. Barriers to using digital tools persist, however, including limited knowledge or skill gaps, he adds.
Moving away from paper-based records and collecting digital data (i.e., digitization) so that it can be used is a crucial early step in digitalization. One of the roadblocks to implementing this shift is that people who are not “digital natives” (generally workers born before 1980) are still most comfortable with paper.
“If a non-digital native is asked a question in an audit, they want to point to data on a piece of paper. A digital native, however, is comfortable with the idea that a picture stored in the cloud and viewed on a device is tangible evidence,” suggests Langer. He says that a picture of a temperature reading or a video of an operator performing a task are examples of digital evidence that can be collected with Tulip’s apps. “We must move beyond a ‘document mindset’. Document-based data—whether on physical paper or a pdf file—can’t be mined the way digital data can,” says Langer.
Langer adds that in Pharma 4.0, all digitalization software will use the cloud, and eventually it will look different from the current MES and enterprise resource planning software. “In the new paradigm, programs will be app-based, intuitive, and democratized so that anyone can use them. All programs will reside in the cloud, and people will use devices in the edge to interact with data in the cloud,” he explains.
This shift is happening, says Bryon Hayes, director of smart manufacturing solutions at Grantek. “Companies are moving from ‘paper on glass’ toward a vertically integrated approach,” Hayes explains. “Many companies see the value of having a cloud-hosted data hub from which they can run analytics or populate dashboards.”
Rodriguez adds that, based on Axendia’s research and interactions with FDA officials, industry executives, and MES software vendors, “we are finally seeing a much-needed shift from paper batch records to implementing MES and electronic batch records (EBR) in support of release/review by exception.” Axendia’s research found that 32% of companies surveyed plan to digitally streamline batch execution and release in the next two years (1).
Automating EBR review is a key benefit of modernizing manufacturing operations, but some companies have held back because of misconceptions regarding FDA’s acceptance of review by exception, says Rodriguez. “In an Axendia ‘Straight from the Source’ webcast , Francisco (Cisco) Vicenty, program manager, case for quality at FDA, debunked many industry myths including that the agency requires EBR print outs for official records and the agency requires validation of every feature in MES.”
Another misconception is that cloud storage could raise data integrity concerns not found in on-premise storage methods. To the contrary, says Bruwer, “cloud-based solutions reduce data integrity challenges by having the cloud data repository be the single source of the truth, with global access easily and securely provided to properly authenticated individuals. In addition, cloud service providers have the critical mass to ensure cutting-edge cyber-security technology and best practices are employed, which an IT department at a bio/pharma company or contract development and manufacturing organization may be more challenged to deliver, especially at smaller organizations with smaller budgets. Similarly, the software underpinning the data warehousing solution can more easily be kept current in a centralized cloud environment versus across multiple servers distributed geographically.”
Bruwer reports that survey respondents in an AspenTech study performed in collaboration with FT Longitude (3) listed cloud and software-as-a-service as key initiatives to improve operational agility in the next three to five years. “Pharma and biopharma companies are looking for long-term technology partnerships with key vendors rather than transactional software purchases,” concludes Bruwer.
Bruwer says that a data integrity challenge—in the cloud or in on-premise storage—can arise if data sources are integrated point-to-point, with many bespoke OT-IT connections accruing across sites. “These disparate implementations can become unmanageable over time, increasing the risk for data corruption,” he explains. “In response, the robust way to ensure long-term data integrity and regulatory compliance over a growing number of OT and IT nodes is to implement an intermediary data platform that
connects the disparate data sources, securely bridging firewalls, contextualizing and cleansing data in transit, and reliably delivering it to a centralized repository that provides a single source of the truth.”
Digitalization is important not only for GxP manufacturing processes, but also for process development and efficient technical transfer. “Documents and spreadsheets tend to be the norm for data collection, process knowledge capture, and the technical transfer process between the lab and production floor,” says Rodriguez. She adds, however, that there is a growing need to eliminate paper and manual processes to meet the increasing pressure to get to market faster. The ongoing shift to broader product mix portfolios, which include large-molecule products and smaller production volumes, adds to the need for digitalization.
Digital product lifecycle management (PLM) tools can accelerate commercialization and improve knowledge transfer (4). “With product and process data predominantly stored across siloed systems and paper on glass documents, data [are] difficult to maintain, reuse, and share with stakeholders across extended, global value chains,” says Rodriguez. “Managing data in a system like PLM helps biopharma companies transition from document-centric to data-centric materials and process knowledge management, establishing a seamless data flow from lab to plant. Structured data [are] easily and quickly evolved and enriched throughout the product lifecycle as the process moves across functional stakeholders, systems, and sites, both internal and external.”
Bruwer reports that nearly half of the 400 pharma professionals surveyed by AspenTech (3) listed data silos between departments as a challenge in digital transformation. “[These divides] can hinder effective information sharing across the product lifecycle, including during technology transfer and commercial manufacturing,” explains Bruwer.
In the new Pharma 4.0 paradigm, knowledge can be stored as data in a repository (i.e., a data lake) that can be mined by digital tools, adds Langer.
Software validation is moving into “Validation 4.0” with the use of computer software assurance (CSA) processes to achieve computer system validation. “Software that can be validated for intended use instead of following the traditional stepwise process will be prominent in life science manufacturing in 2023,” predicts Langer. In CSA, the burden falls on the software providers to show that critical data have integrity and are controlled, and manufacturers demonstrate control of their process using the software, he explains. “The new CSA methods use risk-based approaches to reduce the validation burden by orders of magnitude,” says Langer.
Pharma 4.0 technologies are also being applied to CPV, to enable predictive monitoring of manufacturing processes. “The cloud is a huge enabler for CPV,” says Hayes. “It’s elastic, so resource-intensive applications like CPV are perfect for the cloud. Gathering, storing, contextualizing, and analyzing large volumes of data requires heavy storage, memory, and processing power, and the cloud can scale up and down as needed.” Hayes says that the quality team should first identify their needs and then digital solutions can be found to meet these requirements. “Keep in mind that CPV is a quality-led function that is supported by technology, and not the other way around,” he cautions.
Perceptions are beginning to shift toward greater acceptance, according to AspenTech, as only 35% of respondents to their 2022 survey said that the digital transformation process was hindered by risk aversion (3), compared to a 2021 survey in which risk aversion was considered the top barrier among digital culture leaders (5).
Digital transformation is not a simple or quick change. The benefits, however, are clear, and the tools are available.
1. Axendia. Axendia Research Report: The Needle is Moving–Digital Transformation in Life Sciences Manufacturing. September 2022.
2. Axendia.Axendia Straight from the Source Webcast: FDA Debunks Industry Myths on Electronic Batch Records and Review by Exception. February 2021.
3. AspenTech and FT Longitude. Seizing New Opportunities: Pharma’s Roadmap for Smarter Manufacturing. December 2022.
4. Axendia. Axendia Market Research Report: Accelerating Time to Market with Biopharma PLM. January 2023.
5. AspenTech and FT Longitude. Culture Reimagined: How Pharmaceutical Firms Can Use Data and AI with
Jennifer Markarian is manufacturing reporter for Pharmaceutical Technology.
Vol. 47, No. 5
When referring to this article, please cite it as Markarian, J. Envisioning Digital Pharma Manufacturing. Pharmaceutical Technology 2023 47 (5).